The recent proliferation of Wi-Fi access points in wireless local area networks (WLANs) has made it possible for WLAN positioning systems to use the known locations of its access points (APs) to determine the position of a mobile device or station (STA), especially in areas where there is a large concentration of active Wi-Fi access points (e.g., in urban cores, shopping centers, office buildings, and so on). Typically, the APs that form a basic service set (BSS) of a WLAN are connected to a server that can instruct one or more of its APs to determine the distance between itself and the STA. Once the distances between the STA and 3 or more selected APs are determined, the server can calculate the position of the STA relative to the selected APs.
There are a number of different techniques that WLAN positioning systems can employ to determine the distances between its APs and the STA. For example, some WLAN positioning systems use the received signal strength indicator (RSSI) of signals received from the STA as a rough approximation of the distance between the STA and the AP, where a stronger RSSI means that the STA is closer to the AP and a weaker RSSI means that the STA is further from the AP. Unfortunately, RSSI ranging techniques are notoriously inaccurate, for example, because of the difficulty in modeling signal attenuations in indoor environments and because of different RSSI scales employed by various STA vendors.
As a result, many WLAN positioning systems employ round trip time (RTT) techniques to determine the distance between an AP and a STA. For such systems, a selected AP can initiate an RTT ranging operation with the STA by sending a request (REQ) frame to the STA, which in response thereto sends an acknowledgement (ACK) frame back to the AP. An RTT value can be calculated as the difference in time between the time of arrival (TOA) of the ACK frame and the time of departure (TOD) of the REQ frame, and thereafter the RTT value can be correlated to a distance between the AP and the STA. More specifically, the distance (d) between the AP and the STA can be expressed as d=c*tsp/2=c*(RTT−TAT)/2, where c is the speed of light, tsp is the summation of the actual signal propagation times of the REQ and ACK frames, and TAT is the turn-around time (e.g., processing delay) of the STA.
Unfortunately, different make-and-models (and sometimes even same make-and-models) of STAs have different processing delays, and therefore it is difficult for an AP to accurately estimate the correct TAT for a given STA. Further complicating matters, the TAT for a given STA may vary over time, which may introduce additional errors in the calculated RTT value. Thus, because of the large value of c with respect to d, errors in the calculated value of RTT resulting from slight errors in the estimated TAT of the STA can lead to large errors in the calculated distance between the AP and the STA.
To avoid errors associated with estimating the STA's TAT, other WLAN positioning systems employ time difference of arrival (TDOA) techniques instead of RTT techniques to calculate the distances between its APs and the STA. For such systems, the STA broadcasts a data frame (e.g., a multicast frame), and each of a selected number of APs records the TOA of the data frame received by the AP. Then, differences in the measured TOA values at a multitude of APs can be used to calculate the position of the STA. Thus, because TDOA techniques call for the selected APs to record only TOA values (e.g., rather than calculating RTT values), STA positioning information calculated using TDOA techniques is not subject to errors associated with estimating the TAT of the STA.
However, the TOA values recorded by the selected APs are subject to errors resulting from multipath effects and/or from imperfect timing synchronization between the selected APs. Indeed, because each conventional TDOA measurement involves two different APs each measuring the TOA of a same data frame transmitted from the STA, even slight mismatches between the clocks of the two APs can lead to large errors in position determination. Unfortunately, providing highly accurate and tightly synchronized clocks in a plurality of APs is not only difficult but also very expensive.
Thus, it is desirable to improve the accuracy of WLAN positioning systems.